Applying Dynamic Mode Decomposition for Real-Time Modal Identification of Converter-Driven Oscillation

The integration of inverter-based resources (IBRs) into power systems is a critical step towards a sustainable energy future. However, this integration introduces new challenges for grid stability, particularly through converter-driven oscillations that can threaten the integrity of power systems. The complexity of converter dynamics and non-availability of accurate mathematical model poses significant challenge for power system engineers and researchers to analyze them. Dynamic Mode Decomposition (DMD) emerges as a valuable tool for power system engineers to overcome the challenge of dynamic modelling complexity of these large-scale power systems. DMD is now gaining traction in power system analysis for its ability to identify complex system behaviors without relying on detailed equations. This technique is particularly adept at identifying modal characteristics of converter-driven oscillations, which is crucial for the development of strategies to mitigate their impact. As DMD is still in the early stages of application in power systems, its full potential is yet to be realized. Nevertheless, its promise lies in its capacity to enhance grid security and resiliency by providing a deeper understanding of the spatial-temporal dynamics introduced by large-scale sparse renewable integration. This study explores the application of DMD in modal identification of converter-driven oscillation, highlighting its relevance and adaptability in addressing the challenge of converter-driven oscillation in IBR dominated grid.